About

Beronda L. Montgomery is a plant biologist and researcher who writes books for a general audience. She is the 2025–2026 Sally Starling Seaver Fellow at Radcliffe Institute for Advanced Study at Harvard University. Montgomery's work involves bringing together science and writing in a different communication style, which has inspired her mentees, including Radcliffe Research Partner Serafina Cortez. Montgomery's research and mentorship focus on interdisciplinary approaches, combining biology with communication, and she is recognized for her contributions to fostering connections across disciplines.

Research topics

• Sociology
• Computer Science
• Political Science
• Management
• Library science
• World Wide Web
• Engineering
• Public relations

Selected publications

• Is AI Good for Society?

  Harvard Data Science Review · 2025-05-31

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

• Amid Advancement, Apprehension, and Ambivalence: AI in the Human Ecosystem

  Harvard Data Science Review · 2024-08-01 · 2 citations

  articleOpen access1st authorCorresponding

  This panel was part of the 5th Anniversary Symposium of Harvard Data Science Review—AI and Data Science: Integrating Artificial and Human Ecosystems. The panel explored AI’s impact on society—the intriguing, the scary, and intersection of AI and the public interest. At this moment in history, it's important for us to understand not just the power and potential of AI, but the peril of AI as well. In the face of powerful and disruptive innovation, what do we need to do to ensure that society thrives? How does AI perturb our economy? How does it change our legal system? How does it impact our culture? How does AI change our relationships with one another? The text has been edited for readability and length.

  PublisherOA PDFDOI

• Why are so many big tech whistleblowers women? Here is what the research shows

  2022-06-06 · 1 citations

  preprint1st authorCorresponding
  PublisherDOI

• The impact universe—a framework for prioritizing the public interest in the Internet of Things

  Patterns · 2022-01-01 · 7 citations

  reviewOpen access1st authorCorresponding

  The connected technologies of the Internet of Things (IoT) power the world we live in. IoT systems and devices are critical infrastructure-they provide a platform for social interaction, fuel the marketplace, enable the government, and control the home. Their increasing ubiquity and decision-making capabilities have profound implications for society. When humans are empowered by technology and technology learns from experience, a new kind of social contract is needed, one that specifies the roles and rules of engagement for a cyber-social world. In this paper, we describe the "impact universe," a framework for assessing the impacts and outcomes of potential IoT social controls. Policymakers can use this framework to guide technological innovation so that the design, use, and oversight of IoT products and services advance the public interest. As an example, we develop an impact universe framework that describes the social, economic, and environmental impacts of self-driving cars.

  PublisherOA PDFDOI

• The People Machine: The Earliest Machine Learning?

  Harvard Data Science Review · 2021-01-29

  articleOpen access1st authorCorresponding

  In September 2020, the Harvard Data Science Initiative <https://datascience.harvard.edu/> (HDSI) invited Jill Lepore and Fran Berman to a special event to talk about data science and the Simulmatics Corporation, the focus of Jill’s new book If Then: How the Simulmatics Corporation Invented the Future. Jill’s book tells the compelling story of one of the first corporations to use the power of digital data to both understand and illuminate the world around us, as well as to manipulate the population and skew behavioral outcomes, a kind of power hyped as “the People Machine” by Simulmatics’ PR team. The conversants, data scientist Fran Berman and writer and historian Jill Lepore, had met as Radcliffe Fellows <https://www.radcliffe.harvard.edu/fellowship-program> in 2019 and are both passionate about the societal impacts of technology. They were delighted to carry on their conversation, started at Radcliffe, about data, society, information, truth and trust at the HDSI event. This piece is an edited and streamlined version of their HDSI discussion, whose live video recording can be found below.

  PublisherOA PDFDOI

• The Research Data Alliance: Benefits and Challenges of Building a Community Organization

  Harvard data science review · 2020 · 29 citations

  1st authorCorresponding
  • Sociology
  • Computer Science
  • Political Science

  The Research Data Alliance (RDA) is a community-driven organization dedicated to the development and use of technical, social, and community infrastructure promoting data sharing and data-driven exploration. RDA is particularly important for the global academic community where research infrastructure is often ad hoc, may have a short shelf-life, and hard to fund.At its launch in 2013, RDA struck a chord. Since then, RDA has attracted more than 9400 members from 130-plus countries and developed infrastructure used by groups all over the world. One of its founders is Francine Berman (FB), 2019–2020 Radcliffe Fellow at Harvard and the Edward P. Hamilton Distinguished Professor of Computer Science at Rensselaer Polytechnic Institute. Berman served as co-chair of RDA’s leadership council and chair of the U.S. region of RDA (RDA/US) for the first 6 years of RDA’s growth. Her leadership and organizational experience in developing and operating national-scale cyberinfrastructure (she is former director of the San Diego Supercomputer Center) and her broad community contributions have helped drive the success of RDA.In this piece, Berman is interviewed by Mercè Crosas, Harvard University’s Research Data Officer with the Chief Information Officer’s leadership team and leader of Dataverse. Berman and Crosas met through RDA and both have deep knowledge of the benefits and challenges of running a community-focused organization. They share some of those insights in the conversation below. More information, including specifics on the RDA community and RDA’s ‘origin story,’ can be found here <https://www.rd-alliance.org/sites/default/files/attachment/RDA%20RETROSPECTIVE%20FINAL%20-%20HDSR.pdf> .

  PublisherOA PDFDOI

• The tech field failed a 25-year challenge to achieve gender equality by 2020 – culture change is key to getting on track

  2020-08-26

  preprint1st authorCorresponding
  PublisherDOI

• Cyberspace is critical infrastructure – it will take effective government oversight to make it safe

  2020-08-10 · 1 citations

  preprint1st authorCorresponding
  PublisherDOI

• Realizing the potential of data science

  Communications of the ACM · 2018-03-26 · 112 citations

  article1st authorCorresponding

  Data science promises new insights, helping transform information into knowledge that can drive science and industry.

  PublisherDOI

• What Do We Know about the Stewardship Gap

  Data Science Journal · 2018-01-01 · 9 citations

  articleOpen accessSenior author

  <p class="p1">In the 21^st century, digital data drive innovation and decision-making in nearly every field. However, little is known about the total size, characteristics, and sustainability of these data. In the scholarly sphere, it is widely suspected that there is a gap between the amount of valuable digital data that is produced and the amount that is effectively stewarded and made accessible. The Stewardship Gap Project (<a href="http://bit.ly/stewardshipgap">http://bit.ly/stewardshipgap</a>) investigates characteristics of, and measures, the stewardship gap for sponsored scholarly activity in the United States. This paper presents a preliminary definition of the stewardship gap based on a review of relevant literature and investigates areas of the stewardship gap for which metrics have been developed and measurements made, and where work to measure the stewardship gap is yet to be done. The main findings presented are 1) there is not one stewardship gap but rather multiple “gaps” that contribute to whether data is responsibly stewarded; 2) there are relationships between the gaps that can be used to guide strategies for addressing the various stewardship gaps; and 3) there are imbalances in the types and depths of studies that have been conducted to measure the stewardship gap.

  PublisherOA PDFDOI

Recent grants

• RCN: Building the Research Data Alliance Community through US and International Engagement (RDA 2)

  NSF · $6.0M · 2013–2021

• Application-Level Scheduling with AppLeS

  NSF · $597k · 1997–2001

• National Partnership for Advanced Computational Infrastructure

  NSF · $259.7M · 1997–2005

Frequent coauthors

• Henri Casanova

  18 shared

• Mercè Crosas

  Quantitative BioSciences

  10 shared

• Rich Wolski

  University of California, Santa Barbara

  9 shared

• Alan Su

  University of Computer Studies Yangon

  7 shared

• John May

  7 shared

• Marcio Faerman

  Ohio Supercomputer Center

  6 shared

• Jennifer M. Schopf

  Indiana University Bloomington

  6 shared

• Shava Smallen

  6 shared

Awards & honors

• Inaugural recipient of the ACM/IEEE-CS Ken Kennedy Award for…
• 2019-2020 Katherine Hampson Bessell Fellow at the Radcliffe…
• Member of the National Council on the Humanities (nominated…
• Elected to membership in the American Academy of Arts and Sc…
• Fellow of the National Academy of Public Administration (202…